We will adapt 96 replicate populations of yeast (plus controls) to four environmental stressors for 1500 generations. Unlike a typical yeast/microbial experimental evolution experiment recombination will take place once every 30 generations during evolution. When evolution is complete, each population will be resequenced and the allele frequency of every SNP in the genome estimated at several time-points. Theory, preliminary data, and simulations suggest that the combination of an outbred population, recombination, 1500 generations of evolution, and 96-fold experimental replication will allow us to reliably identify a small number of Candidate Causative Polymorphisms (CCPs) as likely being causative. We will then use site-specific in vivo mutagenesis for 48 CCPs to prove a subset are causative. Experimental work will provide unprecedented insight into how adaptation takes place at the molecular level in outbred sexual species. The results of this work will significantly impact two broad areas of research. First, experiments will rigorously evaluate the ability of evolve and resequence (E&R) experiments to identify causative genes and sites important in adaptation at the molecular level. Furthermore, we will be able to empirically evaluate optimal experimental designs that will enable high power E&R experiments in other systems, as well as population genetics approaches designed to identify genetic signatures of adaptation in polymorphism/divergence data. Second we can directly address several long-standing questions regarding the molecular basis of adaptation. What is the role of standing variation versus de novo mutations in short-term adaptation? Are variants typically regulatory or coding? Is evolution from standing variation typically highly replicable (it isn't under asexual experimental evolution)? Or is evolution initially replicable, then much more heterogeneous? Are the selection coefficients associated with alleles involved in adaptation generally static or dynamic (i.e. does allele frequency change stall out)? Open sharing of all data and strains will allow the broader community to use this resource to empirically test other important hypotheses about the nature of adaptation in sexual outbreds.